Normalize "EXAMPLE::"

src/fpylll/algorithms/babai.py

@@ -24,7 +24,7 @@ def babai(B, t, *args, **kwargs):
     This implementation is more numerically stable compared to the one offered by `MatGSO.babai()`.
     On the other hand, this implementation will only accept tatgets with Integer coefficients.
 
-    EXAMPLE ::
+    EXAMPLE::
 
        >>> from fpylll import *
        >>> n = 10

src/fpylll/fplll/svpcvp.pyx

@@ -174,7 +174,7 @@ def closest_vector(IntegerMatrix B, t, method="fast", int flags=CVP_DEFAULT):
     :param int flags: Either ``CVP.DEFAULT`` or ``CVP.VERBOSE``.
     :returns coordinates of the solution vector:
 
-    EXAMPLE ::
+    EXAMPLE::
 
         >>> from fpylll import *
         >>> FPLLL.set_random_seed(42)

src/fpylll/tools/bkz_simulator.py

@@ -238,7 +238,7 @@ def simulate(r, param):
     :returns: tuple with:
               1. the reduced squared norms of the GSO vectors of the basis,
               2. and the number of BKZ tours simulated.
-    EXAMPLE:
+    EXAMPLE::
         >>> from fpylll import IntegerMatrix, GSO, LLL, FPLLL, BKZ
         >>> FPLLL.set_random_seed(1337)
         >>> A = LLL.reduction(IntegerMatrix.random(100, "qary", bits=30, k=50))
@@ -273,7 +273,7 @@ def simulate_prob(r, param, prng_seed=0xdeadbeef):
     :returns: tuple with:
               1. the reduced squared norms of the GSO vectors of the basis,
               2. and the number of BKZ tours simulated.
-    EXAMPLE:
+    EXAMPLE::
         >>> from fpylll import IntegerMatrix, GSO, LLL, FPLLL, BKZ
         >>> FPLLL.set_random_seed(1337)
         >>> A = LLL.reduction(IntegerMatrix.random(100, "qary", bits=30, k=50))
@@ -304,7 +304,7 @@ def averaged_simulate_prob(r, param, tries=10):
     :returns: tuple with:
               1. averaged reduced squared norms of GSO vectors of the basis,
               2. the averaged number of BKZ tours simulated.
-    EXAMPLE:
+    EXAMPLE::
         >>> from fpylll import IntegerMatrix, GSO, LLL, FPLLL, BKZ
         >>> from fpylll.tools.bkz_simulator import averaged_simulate_prob
         >>> FPLLL.set_random_seed(1337)